
Project Title: Novel Neural Network Architectures for Robust and Explainable Biosensing
- Partner Organisation: WearOptimo
- PhD Candidate at QUT
- Supervisors: Associate Professor Simon Denman, Dr Matt Auburn, Associate Professor Paul Wu
Ben has always had a keen interest in both sport and mathematical modelling. He completed a bachelor’s degree in physics and his research focused on foundational quantum mechanics and theoretical condensed matter. Afterwards, he pursued his passion for trail and ultramarathon running by working as a coach and complemented this by completing a master’s in sports coaching. He is still an avid runner while he pursues his next step in data science.
What made you interested in this program?
The NGGP sports data science program seems like the perfect way to combine my background and interests in sports and mathematical modelling. This program also stood out in the way it combines academia and industry and brings together a cohort of students working on a variety of problems.
What research question are you looking forward to exploring?
I’m excited to delve into how deep learning can improve the use of biosensors and ultimately give people access to live data that has previously not been available. As an athlete and coach, I’ve seen how hydration status can make or break athletes’ performances. So, I’m particularly looking forward to working with WearOptimo on a cutting-edge hydration sensor.
Fun fact about yourself? (write this in 1st person)
If I’m not out running on the trails, then I’m probably spending my free time either freediving or rock climbing.